MSc Business Analytics

Suggested pre-programme reading

We welcome students on to the programme from a range of backgrounds. Offer-holders sometimes ask if there is any preparation they can do before joining the programme. This typically means any suggested pre-reading that you could do to bring yourselves reasonably up to speed on a topic in order to be well-prepared. We recommend that you familiarise yourself with the following material on maths and programming. We have also included some general reading items which you may find interesting.

Maths

You should be familiar with the material in points 1-3

1. Functions

A. General introduction to functions, inverse, composition

• https://www.bbc.co.uk/bitesize/guides/z3brdmn/revision/1
• https://www.bbc.co.uk/bitesize/guides/zrxcqp3/revision/1

B. Logarithmic function

• https://www.bbc.co.uk/bitesize/guides/zn3ty9q/revision/1

C. Trigonometric functions

• https://www.stem.org.uk/resources/elibrary/resource/30363/trigonometry#&gid=undefined&pid=2 
  (preview the material without having to register)
• Derivatives of univariate functions https://www.bbc.co.uk/bitesize/guides/zyj77ty/revision/1

2. Linear Algebra

• Vector arithmetic http://vmls-book.stanford.edu/vmls.pdf Chapter 1.1 up to 1.4
• Matrix arithmetic http://vmls-book.stanford.edu/vmls.pdf Chapter 6.1 up to 6.4

3. Probability

• Basic probability notions https://www.bbc.co.uk/bitesize/guides/zq26y4j/revision/1
• Random variables https://www.probabilitycourse.com/ Chapter 3

If you want to do extra preparation the following online book contains useful material on functions, trigonometry, differentiation, matrices, vectors, logarithms (and exponentials). A University account is required to log in:
https://www.sciencedirect.com/book/9780857092236/fundamentals-of-university-mathematics

Programming

You should be familiar with all the material under “Learn the Basics” from https://www.learnpython.org/  (Hello World – Modules and Packages).

If you want to do extra preparation you can look at this free book https://jakevdp.github.io/PythonDataScienceHandbook/ 

This is the textbook that we will be using in the “Introduction to Computer Science” module (chapters 1-4).

Business

There is no required preparatory reading, but you might be interested in this book that provides helpful background reading - Data Science for Business: What you need to know about data mining and data-analytic thinking by Foster Provost and Tom Fawcett. https://www.oreilly.com/library/view/data-science-for/9781449374273/